This paper reports the description and performance of our system, FBK-HLT, participating in the SemEval 2015, Task #2 "Semantic Textual Similarity", English subtask. We submitted three runs with different hypothesis in combining typical features (lexical similarity, string similarity, word n-grams, etc) with syntactic structure features, resulting in different sets of features. The results evaluated on both STS 2014 and 2015 datasets prove our hypothesis of building a STS system taking into consideration of syntactic information. We outperform the best system on STS 2014 datasets and achieve a very competitive result to the best system on STS 2015 datasets.
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